This episode is brought to you by Augment Code.

You’re a professional software engineer—vibes won’t cut it.
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Building agentic AI apps isn’t just about choosing the best LLM.

Agents need short‑term memory, long‑term recall, and lightning‑fast retrieval. Without it, you’re left with clunky prototypes that never scale.

You know, Redis? The world’s fastest caching solution?

It turns out fast data is the key to good context. And good context is essential for fast, accurate memory. It’s what makes AI agents actually work with your data.

Redis for AI. The right infrastructure. The right tools. The only way to scale.
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Have you tried building a text-to-SQL chatbot?

If your AI agents don’t understand your data – its definitions, queries, and lineage – they’re forced to guess. And bad guesses mean risky assumptions.

That’s where Select Star comes in.

Select Star automatically builds an always-up-to-date knowledge graph of your data – capturing metadata like lineage, usage, and example queries. So whether you’re training an AI model or deploying an agent, your AI can answer with facts, not assumptions.

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